Search engine optimisation: A primer on keyword strategies

Wilson, Ralph F.; Pettijohn, James B.

doi:10.1057/palgrave.dddmp.4340563

Cited by 13 publications

(3 citation statements)

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“…They concluded that SEO is a dynamic process which must be monitored frequently, tracing positive or negative changes for the improvement of a website. Wilson et al (2006) [10] discussed particular SEO techniques that should be implemented during the creation of a website that aim to make the website visible on search engines. In their opinion, keywords must be related to the content of the website so it can be indexed higher in the search results for the targeted keywords.…”

Section: Literature Reviewmentioning

confidence: 99%

Important Factors for Improving Google Search Rank

et al. 2019

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The World Wide Web has become an essential modern tool for people’s daily routine. The fact that it is a convenient means for communication and information search has made it extremely popular. This fact led companies to start using online advertising by creating corporate websites. With the rapid increase in the number of websites, search engines had to come up with a solution of algorithms and programs to qualify the results of a search and provide the users with relevant content to their search. On the other side, developers, in pursuit of the highest rankings in the search engine result pages (SERPs), began to study and observe how search engines work and which factors contribute to higher rankings. The knowledge that has been extracted constituted the base for the creation of the profession of Search Engine Optimization (SEO). This paper consists of two parts. The first part aims to perform a literature review of the factors that affect the ranking of websites in the SERPs and to highlight the top factors that contribute to better ranking. To achieve this goal, a collection and analysis of academic papers was conducted. According to our research, 24 website characteristics came up as factors affecting any website’s ranking, with the most references mentioning quality and quantity of backlinks, social media support, keyword in title tag, website structure, website size, loading time, domain age, and keyword density. The second part consists of our research which was conducted manually using the phrases “hotel Athens”, “email marketing”, and “casual shoes”. For each one of these keywords, the first 15 Google results were examined considering the factors found in the literature review. For the measurement of the significance of each factor, the Spearman correlation was calculated and every factor was compared with the ranking of the results individually. The findings of the research showed us that the top factors that contribute to higher rankings are the existence of website SSL certificate as well as keyword in URL, the quantity of backlinks pointing to a website, the text length, and the domain age, which is not perfectly aligned with what the literature review showed us.

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Section: Literature Reviewmentioning

confidence: 99%

Important Factors for Improving Google Search Rank

et al. 2019

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“…The complexity of these marketing strategies must be analysed in order to understand the new consumer [6,7]. Research has been done on various sustainable search engine initiatives called Green Search Engines in some studies, which are a strategic micro niche within the sector [5,8,9].…”

Section: Introductionmentioning

confidence: 99%

Complexity in the Acceptance of Sustainable Search Engines on the Internet: An Analysis of Unobserved Heterogeneity with FIMIX‐PLS

2018

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This paper analyses the complexity of user behaviour when facing the challenge of using sustainable applications, such as Internet search engines. This paper analyses an acceptance model using extended TAM (Technology Acceptance Model) with Trust as an added external variable. It was suggested that Trust indirectly influences the final Intention to Use with the perceptions of Utility and Ease of Use. To test the proposed model, a survey was carried out with users from different geographical areas of Spain (n=445). The second aim of this study was to understand the complexity of marketing segmentation by separating the application users into different user groups. Users were grouped by their preference of favorite Internet search engine. Unobserved heterogeneity was studied using FIMIX-PLS, and three different user behaviours with search engines were identified. These corresponded to the number of inhabitants who live in the user area. In this way, the impact that the environment has on user choice, acceptance, and use of this type of sustainable applications was shown. The results were checked using PLS-SEM and showed that the model for the adoption of sustainable search engines is explanatory and predictive because confidence and acceptance for this TAM were validated. The conclusions are interesting for developers of environmentally sustainable and responsible applications which want to coincide with current trends to ensure that users prefer them.

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“…For example, if you search for "Westminster Abbey", you will get its information and also a Google Maps location for the same. Internet searches are either factorized based either on their keywords or their sentences (Wilson and Pettijohn, 2006). The task for a user is formulating a moderate set of phrases or keywords that will enable the search engine to pinpoint the most related results.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning as a New Search Engine Interface: An Overview

Neogy

Paruchuri

2014

Eng. int. (Dhaka)

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The essence of a web page is an inherently predisposed issue, one that is built on behaviors, interests, and intelligence. There are relatively a ton of reasons web pages are critical to the new world, as the matter cannot be overemphasized. The meteoric growth of the internet is one of the most potent factors making it hard for search engines to provide actionable results. With classified directories, search engines store web pages. To store these pages, some of the engines rely on the expertise of real people. Most of them are enabled and classified using automated means but the human factor is dominant in their success. From experimental results, we can deduce that the most effective and critical way to automate web pages for search engines is via the integration of machine learning.

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Search engine optimisation: A primer on keyword strategies

Cited by 13 publications

References 1 publication

Important Factors for Improving Google Search Rank

Important Factors for Improving Google Search Rank

Complexity in the Acceptance of Sustainable Search Engines on the Internet: An Analysis of Unobserved Heterogeneity with FIMIX‐PLS

Machine Learning as a New Search Engine Interface: An Overview

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